Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes
Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinfor...
Gespeichert in:
| Veröffentlicht in: | Scientific reports 2016-01, Vol.6 (1), p.19820-19820, Article 19820 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 19820 |
|---|---|
| container_issue | 1 |
| container_start_page | 19820 |
| container_title | Scientific reports |
| container_volume | 6 |
| creator | Saunders, Colleen J. Jalali Sefid Dashti, Mahjoubeh Gamieldien, Junaid |
| description | Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (
COL11A2
,
ELN
,
ITGB3
,
LOX
) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies. |
| doi_str_mv | 10.1038/srep19820 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4726433</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1899046901</sourcerecordid><originalsourceid>FETCH-LOGICAL-c438t-9d0388a4895b0204392536f28ee98a16937f5581bee9e31e41bf817aabafeae93</originalsourceid><addsrcrecordid>eNplkU9rFTEUxYMottQu_AIScKPC0_ybmWQjlGJVKLhQ1-HOzJ1p2kzyTDJKd370prz6eGo2Sbg_Ts7JIeQ5Z285k_pdTrjlRgv2iBwLppqNkEI8PjgfkdOcr1ldjTCKm6fkSLSaKdN1x-T3V1wgFDdQFwqmFGcoLgYaJwp0WX1x9CbEXx7HGekYF3B1Fkr0cXYDeLrEEf09XTCMLsQtlKtb6kasmpPDTKe4JppLimGmA1RmhII0uXxDZwyYn5EnE_iMpw_7Cfl-8eHb-afN5ZePn8_PLjeDkrpszFizalDaND2r0aQRjWwnoRGNBt4a2U1No3lf7yg5Kt5PmncAPUwIaOQJeb_T3a79guNQDSbwdpvcAunWRnD270lwV3aOP63qRKukrAKvHgRS_LFiLnZxeUDvIWBcs-Vdy7QxnVQVffkPel1_IdR4lleEqdYwXqnXO2pIMdcWp70Zzux9tXZfbWVfHLrfk3-KrMCbHZDrKMyYDp78T-0O-jGwuw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1899046901</pqid></control><display><type>article</type><title>Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Springer Nature OA Free Journals</source><source>Nature Free</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><source>Free Full-Text Journals in Chemistry</source><creator>Saunders, Colleen J. ; Jalali Sefid Dashti, Mahjoubeh ; Gamieldien, Junaid</creator><creatorcontrib>Saunders, Colleen J. ; Jalali Sefid Dashti, Mahjoubeh ; Gamieldien, Junaid</creatorcontrib><description>Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (
COL11A2
,
ELN
,
ITGB3
,
LOX
) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/srep19820</identifier><identifier>PMID: 26804977</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/114/2164 ; 631/114/2403 ; 631/208/205 ; 692/4023/1671/1835 ; 692/53/2423 ; Animals ; Bioinformatics ; Collagen Type XI - genetics ; Computational Biology - methods ; Connective tissue diseases ; Data mining ; Databases, Factual ; Genes ; Genetic Association Studies ; Genetic factors ; Genetic Predisposition to Disease ; Genome, Human ; Humanities and Social Sciences ; Humans ; Integration ; Integrin beta3 - genetics ; Mice ; Molecular Sequence Annotation ; multidisciplinary ; Ontology ; Pain ; Questioning ; Rats ; Scavenger Receptors, Class E - genetics ; Science ; Semantics ; Tendinopathy - genetics ; Tendinopathy - metabolism ; Tendinopathy - pathology ; Tendons - metabolism ; Tendons - pathology</subject><ispartof>Scientific reports, 2016-01, Vol.6 (1), p.19820-19820, Article 19820</ispartof><rights>The Author(s) 2016</rights><rights>Copyright Nature Publishing Group Jan 2016</rights><rights>Copyright © 2016, Macmillan Publishers Limited 2016 Macmillan Publishers Limited</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-9d0388a4895b0204392536f28ee98a16937f5581bee9e31e41bf817aabafeae93</citedby><cites>FETCH-LOGICAL-c438t-9d0388a4895b0204392536f28ee98a16937f5581bee9e31e41bf817aabafeae93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726433/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726433/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,862,883,27907,27908,41103,42172,51559,53774,53776</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26804977$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Saunders, Colleen J.</creatorcontrib><creatorcontrib>Jalali Sefid Dashti, Mahjoubeh</creatorcontrib><creatorcontrib>Gamieldien, Junaid</creatorcontrib><title>Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (
COL11A2
,
ELN
,
ITGB3
,
LOX
) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies.</description><subject>631/114/2164</subject><subject>631/114/2403</subject><subject>631/208/205</subject><subject>692/4023/1671/1835</subject><subject>692/53/2423</subject><subject>Animals</subject><subject>Bioinformatics</subject><subject>Collagen Type XI - genetics</subject><subject>Computational Biology - methods</subject><subject>Connective tissue diseases</subject><subject>Data mining</subject><subject>Databases, Factual</subject><subject>Genes</subject><subject>Genetic Association Studies</subject><subject>Genetic factors</subject><subject>Genetic Predisposition to Disease</subject><subject>Genome, Human</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Integration</subject><subject>Integrin beta3 - genetics</subject><subject>Mice</subject><subject>Molecular Sequence Annotation</subject><subject>multidisciplinary</subject><subject>Ontology</subject><subject>Pain</subject><subject>Questioning</subject><subject>Rats</subject><subject>Scavenger Receptors, Class E - genetics</subject><subject>Science</subject><subject>Semantics</subject><subject>Tendinopathy - genetics</subject><subject>Tendinopathy - metabolism</subject><subject>Tendinopathy - pathology</subject><subject>Tendons - metabolism</subject><subject>Tendons - pathology</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNplkU9rFTEUxYMottQu_AIScKPC0_ybmWQjlGJVKLhQ1-HOzJ1p2kzyTDJKd370prz6eGo2Sbg_Ts7JIeQ5Z285k_pdTrjlRgv2iBwLppqNkEI8PjgfkdOcr1ldjTCKm6fkSLSaKdN1x-T3V1wgFDdQFwqmFGcoLgYaJwp0WX1x9CbEXx7HGekYF3B1Fkr0cXYDeLrEEf09XTCMLsQtlKtb6kasmpPDTKe4JppLimGmA1RmhII0uXxDZwyYn5EnE_iMpw_7Cfl-8eHb-afN5ZePn8_PLjeDkrpszFizalDaND2r0aQRjWwnoRGNBt4a2U1No3lf7yg5Kt5PmncAPUwIaOQJeb_T3a79guNQDSbwdpvcAunWRnD270lwV3aOP63qRKukrAKvHgRS_LFiLnZxeUDvIWBcs-Vdy7QxnVQVffkPel1_IdR4lleEqdYwXqnXO2pIMdcWp70Zzux9tXZfbWVfHLrfk3-KrMCbHZDrKMyYDp78T-0O-jGwuw</recordid><startdate>20160125</startdate><enddate>20160125</enddate><creator>Saunders, Colleen J.</creator><creator>Jalali Sefid Dashti, Mahjoubeh</creator><creator>Gamieldien, Junaid</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20160125</creationdate><title>Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes</title><author>Saunders, Colleen J. ; Jalali Sefid Dashti, Mahjoubeh ; Gamieldien, Junaid</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-9d0388a4895b0204392536f28ee98a16937f5581bee9e31e41bf817aabafeae93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>631/114/2164</topic><topic>631/114/2403</topic><topic>631/208/205</topic><topic>692/4023/1671/1835</topic><topic>692/53/2423</topic><topic>Animals</topic><topic>Bioinformatics</topic><topic>Collagen Type XI - genetics</topic><topic>Computational Biology - methods</topic><topic>Connective tissue diseases</topic><topic>Data mining</topic><topic>Databases, Factual</topic><topic>Genes</topic><topic>Genetic Association Studies</topic><topic>Genetic factors</topic><topic>Genetic Predisposition to Disease</topic><topic>Genome, Human</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Integration</topic><topic>Integrin beta3 - genetics</topic><topic>Mice</topic><topic>Molecular Sequence Annotation</topic><topic>multidisciplinary</topic><topic>Ontology</topic><topic>Pain</topic><topic>Questioning</topic><topic>Rats</topic><topic>Scavenger Receptors, Class E - genetics</topic><topic>Science</topic><topic>Semantics</topic><topic>Tendinopathy - genetics</topic><topic>Tendinopathy - metabolism</topic><topic>Tendinopathy - pathology</topic><topic>Tendons - metabolism</topic><topic>Tendons - pathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Saunders, Colleen J.</creatorcontrib><creatorcontrib>Jalali Sefid Dashti, Mahjoubeh</creatorcontrib><creatorcontrib>Gamieldien, Junaid</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Saunders, Colleen J.</au><au>Jalali Sefid Dashti, Mahjoubeh</au><au>Gamieldien, Junaid</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2016-01-25</date><risdate>2016</risdate><volume>6</volume><issue>1</issue><spage>19820</spage><epage>19820</epage><pages>19820-19820</pages><artnum>19820</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (
COL11A2
,
ELN
,
ITGB3
,
LOX
) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>26804977</pmid><doi>10.1038/srep19820</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2045-2322 |
| ispartof | Scientific reports, 2016-01, Vol.6 (1), p.19820-19820, Article 19820 |
| issn | 2045-2322 2045-2322 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4726433 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Springer Nature OA Free Journals; Nature Free; EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection; Free Full-Text Journals in Chemistry |
| subjects | 631/114/2164 631/114/2403 631/208/205 692/4023/1671/1835 692/53/2423 Animals Bioinformatics Collagen Type XI - genetics Computational Biology - methods Connective tissue diseases Data mining Databases, Factual Genes Genetic Association Studies Genetic factors Genetic Predisposition to Disease Genome, Human Humanities and Social Sciences Humans Integration Integrin beta3 - genetics Mice Molecular Sequence Annotation multidisciplinary Ontology Pain Questioning Rats Scavenger Receptors, Class E - genetics Science Semantics Tendinopathy - genetics Tendinopathy - metabolism Tendinopathy - pathology Tendons - metabolism Tendons - pathology |
| title | Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T22%3A29%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Semantic%20interrogation%20of%20a%20multi%20knowledge%20domain%20ontological%20model%20of%20tendinopathy%20identifies%20four%20strong%20candidate%20risk%20genes&rft.jtitle=Scientific%20reports&rft.au=Saunders,%20Colleen%20J.&rft.date=2016-01-25&rft.volume=6&rft.issue=1&rft.spage=19820&rft.epage=19820&rft.pages=19820-19820&rft.artnum=19820&rft.issn=2045-2322&rft.eissn=2045-2322&rft_id=info:doi/10.1038/srep19820&rft_dat=%3Cproquest_pubme%3E1899046901%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1899046901&rft_id=info:pmid/26804977&rfr_iscdi=true |